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Luo Y, Gessler A, D'Odorico P, Hufkens K, Stocker BD. Quantifying effects of cold acclimation and delayed springtime photosynthesis resumption in northern ecosystems. THE NEW PHYTOLOGIST 2023; 240:984-1002. [PMID: 37583086 DOI: 10.1111/nph.19208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 07/24/2023] [Indexed: 08/17/2023]
Abstract
Land carbon dynamics in temperate and boreal ecosystems are sensitive to environmental change. Accurately simulating gross primary productivity (GPP) and its seasonality is key for reliable carbon cycle projections. However, significant biases have been found in early spring GPP simulations of northern forests, where observations often suggest a later resumption of photosynthetic activity than predicted by models. Here, we used eddy covariance-based GPP estimates from 39 forest sites that differ by their climate and dominant plant functional types. We used a mechanistic and an empirical light use efficiency (LUE) model to investigate the magnitude and environmental controls of delayed springtime photosynthesis resumption (DSPR) across sites. We found DSPR reduced ecosystem LUE by 30-70% at many, but not all site-years during spring. A significant depression of LUE was found not only in coniferous but also at deciduous forests and was related to combined high radiation and low minimum temperatures. By embedding cold-acclimation effects on LUE that considers the delayed effects of minimum temperatures, initial model bias in simulated springtime GPP was effectively resolved. This provides an approach to improve GPP estimates by considering physiological acclimation and enables more reliable simulations of photosynthesis in northern forests and projections in a warming climate.
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Affiliation(s)
- Yunpeng Luo
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
- Department of Environmental System Science, Institute of Agricultural Sciences, ETH Zurich, 8902, Zurich, Switzerland
| | - Arthur Gessler
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
| | - Petra D'Odorico
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
| | - Koen Hufkens
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
- Department of Environmental System Science, Institute of Agricultural Sciences, ETH Zurich, 8902, Zurich, Switzerland
| | - Benjamin D Stocker
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
- Department of Environmental System Science, Institute of Agricultural Sciences, ETH Zurich, 8902, Zurich, Switzerland
- Institute of Geography, University of Bern, Hallerstrasse 12, 3012, Bern, Switzerland
- Oeschger Centre for Climate Change Research, University of Bern, Falkenplatz 16, 3012, Bern, Switzerland
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Krishna DK, Watham T, Padalia H, Srinet R, Nandy S. Improved gross primary productivity estimation using semi empirical (PRELES) model for moist Indian sal forest. Ecol Modell 2023. [DOI: 10.1016/j.ecolmodel.2022.110175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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3
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Bayesian multi-level calibration of a process-based maize phenology model. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2022.110154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Vernay A, Tian X, Chi J, Linder S, Mäkelä A, Oren R, Peichl M, Stangl ZR, Tor-Ngern P, Marshall JD. Estimating canopy gross primary production by combining phloem stable isotopes with canopy and mesophyll conductances. PLANT, CELL & ENVIRONMENT 2020; 43:2124-2142. [PMID: 32596814 DOI: 10.1111/pce.13835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/21/2020] [Accepted: 06/22/2020] [Indexed: 06/11/2023]
Abstract
Gross primary production (GPP) is a key component of the forest carbon cycle. However, our knowledge of GPP at the stand scale remains uncertain, because estimates derived from eddy covariance (EC) rely on semi-empirical modelling and the assumptions of the EC technique are sometimes not fully met. We propose using the sap flux/isotope method as an alternative way to estimate canopy GPP, termed GPPiso/SF , at the stand scale and at daily resolution. It is based on canopy conductance inferred from sap flux and intrinsic water-use efficiency estimated from the stable carbon isotope composition of phloem contents. The GPPiso/SF estimate was further corrected for seasonal variations in photosynthetic capacity and mesophyll conductance. We compared our estimate of GPPiso/SF to the GPP derived from PRELES, a model parameterized with EC data. The comparisons were performed in a highly instrumented, boreal Scots pine forest in northern Sweden, including a nitrogen fertilized and a reference plot. The resulting annual and daily GPPiso/SF estimates agreed well with PRELES, in the fertilized plot and the reference plot. We discuss the GPPiso/SF method as an alternative which can be widely applied without terrain restrictions, where the assumptions of EC are not met.
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Affiliation(s)
- Antoine Vernay
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Xianglin Tian
- Department of Forest Sciences, University of Helsinki, Helsinki, Finland
| | - Jinshu Chi
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Sune Linder
- Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Annikki Mäkelä
- Department of Forest Sciences, University of Helsinki, Helsinki, Finland
| | - Ram Oren
- Department of Forest Sciences, University of Helsinki, Helsinki, Finland
- Division of Environmental Science & Policy, Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
- Department of Civil & Environmental Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina, USA
| | - Matthias Peichl
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Zsofia R Stangl
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Pantana Tor-Ngern
- Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
- Environment, Health and Social Data Analytics Research Group, Chulalongkorn University, Bangkok, Thailand
| | - John D Marshall
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden
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